AI is a major focus area of Aalto University and the Department of Computer Science. Building on the department's strong tradition that includes neural network pioneers Teuvo Kohonen and Erkki Oja.
Our research contributes both to the fundamentals of AI across its many subfields, as well as to the accelerating practical impact AI has on businesses and societies.
The Department of Computer Science is a key player in the Finnish Center for Artificial Intelligence FCAI, a major ecosystem of academic, private and public sector partners.
Weekly seminar organised by FCAI.
Mannila left his position as President of the Academy of Finland and began on March 1 as professor at Aalto University, where he last served as Vice President 2010–2012
Aalto University Professor Samuel Kaski has been awarded the Turing AI World-Leading Researcher Fellowship to establish a new center of excellence. The funding relates to Kaski’s work at the University of Manchester, but Finnish research on modeling user intent will also benefit.
With an artificial intelligence (AI) method developed by researchers at Aalto University and University of Helsinki, researchers can now link immune cells to their targets and for example uncouple which white blood cells recognize SARS-CoV-2. The developed tool has broad applications in understanding the function of immune system in infections, autoimmune disorders, and cancer.
Heli Julkunen developed a machine learning method that predicts how different drug combinations kill cancer cells, and now she helps advance preventive healthcare as a data scientist
Neuroscience and neurotechnology are gaining a fresh ally in the form of artificial intelligence, which can assess dementia risk and enhance the effectiveness of depression treatments.
The magazine pays tribute to the development of a model that starkly reduces the amount of data needed for generating new, artificial images
The A.I. and Software Systems (AISS) research group focuses on computing technologies for designing, building and managing intelligent systems.
Machine learning models and methods for big data over networks
We develop new methods for probabilistic modeling, Bayesian inference and machine learning. Our current focuses are in particular learning from multiple data sources, Bayesian model assessment and selection, approximate inference and information visualization.
Research on semantic technologies, such as the Semantic Web and intelligent web services.
Collaborative institute for research on information technology.
International research hub for artificial intelligence
Research areas in the Department of Computer Science
To foster future science and society.
Science for tomorrow’s technology, innovations and businesses
